Digital image manipulation is an integral part of the production process in many industries. For example, graphic artists, computer animators, scientists and many other computer users frequently utilize various tools for performing digital image manipulation. Such users have access to a variety of image processing tools. Each image-processing tool utilizes one or more image processing techniques to achieve a specific goal, although, to accomplish any given image-processing task, users are frequently required to combine a number of different image processing tools.
Most image processing techniques require a substantial amount of computing power. Whether image-processing techniques are used interactively or automatically, the computation time required to complete a task may hinder the task itself, especially when the amount of data to be processed is very large.
One way to speed up image processing is to increase the hardware performance by implementing faster electronic chips and/or scaling up the number of processors running the task. However, this solution can be prohibitively expensive. Another way of increasing the processing speed is to utilize alternative and faster processing methods that produce the same results as the existing ones. This is typically accomplished by improving the execution time of the underlying algorithm associated with the image processing technique that is being performed.
An example of an image processing technique, that is computationally intensive, is referred to by those of ordinary skill in the art as a median filter. In the image processing field median filters provide a mechanism for processing an image in such a way that each resulting value equals the numerical median of the source values within a given radius. A problem most users encounter is that existing median filters take prohibitively long to process an image. The slow processing speed is a result of inefficiencies in the underlying algorithm. Therefore, there is a need to improve processing speeds by eliminating these inefficiencies. As is discussed in more detail below, embodiments of the invention provide a technique for increasing the speed of image processing algorithms, such as the median filter, through the use of a more efficient processing methodology.